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Record Nr. |
UNINA9910154693203321 |
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Autore |
Ahmed Sara <1969-> |
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Titolo |
Living a feminist life / / Sara Ahmed |
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Pubbl/distr/stampa |
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Durham : , : Duke University Press, , 2017 |
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ISBN |
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9780822363040 |
9780822363194 |
9780822373377 |
0822373378 |
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Descrizione fisica |
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1 online resource (xi, 299 pages) : ill |
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Classificazione |
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Disciplina |
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Soggetti |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Feminism is sensational -- On being directed -- Willfulness and feminist subjectivity -- Trying to transform -- Being in question -- Brick walls -- Fragile connections -- Feminist snap -- Lesbian feminism -- Conclusion 1: A killjoy survival kit -- Conclusion 2: A killjoy manifesto. |
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Sommario/riassunto |
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In Living a Feminist Life Sara Ahmed shows how feminist theory is generated from everyday life and the ordinary experiences of being a feminist at home and at work. Building on legacies of feminist of color scholarship in particular, Ahmed offers a poetic and personal meditation on how feminists become estranged from worlds they critique—often by naming and calling attention to problems—and how feminists learn about worlds from their efforts to transform them. Ahmed also provides her most sustained commentary on the figure of the feminist killjoy introduced in her earlier work while showing how feminists create inventive solutions—such as forming support systems—to survive the shattering experiences of facing the walls of racism and sexism. The killjoy survival kit and killjoy manifesto, with which the book concludes, supply practical tools for how to live a feminist life, thereby strengthening the ties between the inventive |
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creation of feminist theory and living a life that sustains it. |
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2. |
Record Nr. |
UNINA9911047814303321 |
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Autore |
Kakarla Jagadeesh |
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Titolo |
Computer Vision and Image Processing : 9th International Conference, CVIP 2024, Chennai, India, December 19–21, 2024, Revised Selected Papers, Part IV / / edited by Jagadeesh Kakarla, R. Balasubramanian, Subrahmanyam Murala, Santosh Kumar Vipparthi, Deep Gupta |
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Pubbl/distr/stampa |
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Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2026 |
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ISBN |
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Edizione |
[1st ed. 2026.] |
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Descrizione fisica |
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1 online resource (713 pages) |
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Collana |
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Communications in Computer and Information Science, , 1865-0937 ; ; 2476 |
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Altri autori (Persone) |
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BalasubramanianR |
MuralaSubrahmanyam |
VipparthiSantosh Kumar |
GuptaDeep |
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Disciplina |
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Soggetti |
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Image processing - Digital techniques |
Computer vision |
Artificial intelligence |
Social sciences - Data processing |
Data protection |
Education - Data processing |
Computer Imaging, Vision, Pattern Recognition and Graphics |
Artificial Intelligence |
Computer Application in Social and Behavioral Sciences |
Data and Information Security |
Computers and Education |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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-- Analysis of Chromatic Response of EEG Signals Induced for Primary Color Visualization. -- ReConfNET: Confidence-Driven Hierarchical Indoor Scene Reconstruction. -- On Tree Mango Fruit Yield Estimation |
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using Graph Cuts and Depth First Search. -- Leveraging GANs for Chest X-ray Image Synthesis. -- Early Violence Recognition using Knowledge Distillation. -- MiXceptionLeaf: A Novel Model for Cassava Leaf Disease Classification Using XceptionNet and ConvMixer Layer. -- Optimizing Image Captioning using BLIP Framework with Advanced Processing of DWT LL Band-Compressed Images. -- Robust Denoising in Fringe Projection Profilometry: A Poissonian-Gaussian Approachwith Lightweight Neural Networks. -- A retinex driven fractional-order regularization model for despeckling and enhancing of Synthetic Aperture Radar images. -- Customized Self-Configuring U-Net Framework for Anatomical Lesion Segmentation in Post-Stroke Brain MRI. -- Plant Leaf Diseases classification using Knowledge Distillation Methodologies. -- TDIUC-AVQA: A Visual Question Answering Dataset in Low-Resource Assamese Language. -- Joint compression of multi-model systems for edge devices. -- VLRASN-112: A Visual Lip Reading Dataset for Assamese Compound Numeric Sequence Recognition. -- Multimodal Deep Learning Framework for Skin Lesion Classification. -- Enhancing Diagnostic Precision: AI-Based Differentiation of Brain Tumors and Multiple Sclerosis. -- CubeMin: Fingerprint Indexing Scheme using Pairwise Minutia Feature in Cubic Space. -- Unconstrained Low-Resolution Face Recognition using Attention Network and Resolution Aware Images. -- An Instance-Aware Attention Vision Transformer for Glaucoma Detection using Retinal Fundus Image Analysis. -- Improved Image data augmentation using Dynamic Mode Decomposition. -- Assessment of the Impact of D-Adaptation on Convolutional Image Classification. -- An Efficient Hybrid Feature Selection Approach for Offline Handwritten Mathematical Symbol Recognition. -- Single Image Super-Resolution: Use of Transformer with Multiple Attention modules. -- MSPlantNet: Plant Disease Classification using Few Shot Learning. -- PATROL’S PAL: Anomaly Face Recognition from Low-Quality CCTV Footage. -- Skeleton-Based Action Recognition - Dual Stream Learning of Discriminative Representations. -- Leveraging Biogeography-based Optimization for Band Selection in Hyperspectral Brain Imaging: a CNN-based Classification Framework. -- RWAEFA: Random Walk-based Artificial Electric Field Optimization Algorithm - An Application towards Feature Selection for Cytology Image Classification. -- Super-resolution Enhanced Tree Classification in Satellite Images Using Convolutional Neural Networks. -- Prediction of Short-Term Traffic Flow Using a Hybrid Architecture. -- Enhanced Semantic-Driven Anomaly Detection: A Multi-Class Strategy for Video Data. -- Activity Recognition in Smart Homes with Knowledge Graph and Attention-Guided Learning. |
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Sommario/riassunto |
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The Six-volume proceedings set CCIS 2473 and 2478 constitutes the refereed proceedings of the 9th International Conference on Computer Vision and Image Processing, CVIP 2024, held in Chennai, India, during December 19–21, 2024. The 178 full papers presented were carefully reviewed and selected from 647 submissions.The papers focus on various important and emerging topics in image processing, computer vision applications, deep learning, and machine learning techniques in the domain. |
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